> For the complete documentation index, see [llms.txt](https://docs.groundcover.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.groundcover.com/collect-data/byoc/setup-byoc-with-gcp/enable-ai-models-for-agent-mode.md).

# Enable AI models for Agent Mode

Enable your selected models in Vertex AI for a GCP BYOC deployment.

Before adding models to groundcover, make sure you have access to them in your BYOC project's configured Vertex AI region.

## Check the configured region

All Vertex AI models in a backend use the same configured region. groundcover displays this region beside the provider name in **Settings > AI & Agents > Management**.

## Enable your selected models

The screenshots show a Claude partner-model enablement flow as an example. Choose your own model and configured region; Google and partner models may have different enablement steps.

1. Open your BYOC project in the Google Cloud console and go to **Vertex AI > Model Garden**.

   <figure><img src="https://2771001740-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FUHgqKYgCiRKdOpWQdi52%2Fuploads%2FLkkC576BLuZqS3LlKM5F%2FScreenshot%202026-03-29%20at%2011.47.38.png?alt=media&amp;token=fc6aa2f9-003a-430c-96b5-3d473f77b43a" alt="Search for Model Garden in the Google Cloud console."><figcaption></figcaption></figure>
2. Find the model you want to use and review its supported locations and access requirements.

   <figure><img src="https://2771001740-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FUHgqKYgCiRKdOpWQdi52%2Fuploads%2FQZbZlAX5IFxGgxBot2cB%2FScreenshot%202026-03-29%20at%2011.48.45.png?alt=media&amp;token=4eae012e-3d17-4a67-8475-c8e3e801c346" alt="Search for a model in Vertex AI Model Garden."><figcaption><p>Search for the model you want to enable; Claude is shown as an example.</p></figcaption></figure>
3. If the model requires enablement, open its page and click **Enable**.

   <figure><img src="https://2771001740-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FUHgqKYgCiRKdOpWQdi52%2Fuploads%2F1w6Ykn8b9vHGQbqnOYkp%2FScreenshot%202026-03-29%20at%2011.49.37.png?alt=media&amp;token=81d49e92-0a26-406c-8649-0c7558b2118a" alt="The Enable button on a partner model&#x27;s page."><figcaption></figcaption></figure>
4. Complete any required use-case details, then click **Next**.

   <figure><img src="https://2771001740-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FUHgqKYgCiRKdOpWQdi52%2Fuploads%2FHCYj5GHMyyDGpmKf3ze7%2FScreenshot%202026-03-29%20at%2011.50.43.png?alt=media&amp;token=f96bc475-7fa7-413e-9903-913a69e637d5" alt="Example partner-model enablement form with business and use-case fields."><figcaption></figcaption></figure>
5. If prompted for **Location**, select your backend's configured region. Ensure the model supports that region.

   <figure><img src="https://2771001740-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FUHgqKYgCiRKdOpWQdi52%2Fuploads%2FUHwBWsVES8kPlWGrqL34%2FScreenshot%202026-03-29%20at%2011.51.50.png?alt=media&amp;token=8a6f5a97-34cf-4480-8385-2ae7a49f6c2b" alt="Location selection in the model enablement flow."><figcaption><p>The screenshot shows global. Use it only if your backend is configured for global.</p></figcaption></figure>
6. Review any required publisher terms and agreements, then click **Agree**.

   <figure><img src="https://2771001740-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FUHgqKYgCiRKdOpWQdi52%2Fuploads%2FX7iiHF0QaE2JrYPVPzGt%2FScreenshot%202026-03-29%20at%2011.52.07.png?alt=media&amp;token=1deef2b0-8399-46b0-93e2-31c1915114f0" alt="Review and accept the partner model&#x27;s terms and agreements."><figcaption></figcaption></figure>

Repeat for each model you want to enable.

See Google's [Model Garden guide](https://cloud.google.com/vertex-ai/generative-ai/docs/model-garden/explore-models) and [Marketplace model enablement guide](https://cloud.google.com/marketplace/docs/enable-ai-models) for provider-specific steps.

## Use the models in groundcover

Cloud access and the models enabled in groundcover are separate settings. In [model management](/automate/agent-mode/configuring-settings.md#manage-models), select or enter the model IDs under **Enabled models**, choose a **Default model**, and select **Save**. Suggestions are checked against your configuration; they are not a complete list of models in your cloud account. You can also enter a supported model ID manually.

If validation fails, use the provider error to check the model ID, configured region, access, and permissions. Refresh the suggestions after changing cloud access, then save again. A failed save leaves the existing configuration active.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.groundcover.com/collect-data/byoc/setup-byoc-with-gcp/enable-ai-models-for-agent-mode.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
